PERAMALAN HARGA BATU BARA ACUAN MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE DAN FUNGSI TRANSFER

Suci Pujiani Prahesti (Department of Statistics, IPB University, Indonesia)
Itasia Dina Sulvianti (Department of Statistics, IPB University, Indonesia)
Yenni Angraini (Department of Statistics, IPB University, Indonesia)

Xplore: Journal of Statistics
Vol. 12 No. 1 (2023): Vol. 12 No. 1 (2023)

Indonesia as one of the largest coal producing countries in the world has an important role in coal global demand. Currently, most countries in Europe are turning to coal as a source of electricity. This is due to Covid-19 pandemic and the conflict between Russia and Ukraine which endangers energy sources. Therefore, forecasting coal prices in the future is needed to determine the right policy in dealing with the large demand for coal. Coal price fluctuation are influenced by several factors such as the prices of the other commodities instance natural gas price. The natural gas price factor will be modeled in coal price forecasting using the transfer function method as the input series. This study compares the ARIMA and Transfer Function in coal price forecasting. The results showed that MAPE values of ARIMA and transfer function method are 23,14% and 17,66%. Based on MAPE values that forecasting using the transfer function method has a better ability than ARIMA method in forecasting coal prices.